AIMC Topic: Bangladesh

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Sociodemographic risk factors of under-five stunting in Bangladesh: Assessing the role of interactions using a machine learning method.

PloS one
This paper aims to demonstrate the importance of studying interactions among various sociodemographic risk factors of childhood stunting in Bangladesh with the help of an interpretable machine learning method. Data used for the analyses are extracted...

Application of stacking hybrid machine learning algorithms in delineating multi-type flooding in Bangladesh.

Journal of environmental management
Floods are among the most devastating natural hazards in Bangladesh. The country experiences multi-type floods (i.e., fluvial, flash, pluvial, and surge floods) every year. However, areas prone to multi-type floods have not yet been assessed on a nat...

Machine learning algorithm for characterizing risks of hypertension, at an early stage in Bangladesh.

Diabetes & metabolic syndrome
BACKGROUND AND AIMS: Hypertension has become a major public health issue as the prevalence and risk of premature death and disability among adults due to hypertension has increased globally. The main objective is to characterize the risk factors of h...

Model and variable selection using machine learning methods with applications to childhood stunting in Bangladesh.

Informatics for health & social care
Childhood stunting is a serious public health concern in Bangladesh. Earlier research used conventional statistical methods to identify the risk factors of stunting, and very little is known about the applications and usefulness of machine learning (...

Machine learning algorithms for predicting malnutrition among under-five children in Bangladesh.

Nutrition (Burbank, Los Angeles County, Calif.)
OBJECTIVE: The aim of this study was is to predict malnutrition status in under-five children in Bangladesh by using various machine learning (ML) algorithms.

Automated detection and classification of diabetes disease based on Bangladesh demographic and health survey data, 2011 using machine learning approach.

Diabetes & metabolic syndrome
BACKGROUND AND AIMS: Diabetes has been recognized as a continuing health challenge for the twenty-first century, both in developed and developing countries including Bangladesh. The main objective of this study is to use machine learning (ML) based c...

Artificial neural network model to predict transport parameters of reactive solutes from basic soil properties.

Environmental pollution (Barking, Essex : 1987)
Measurement of solute-transport parameters through soils for a wide range of solute- and soil-types is time-consuming, laborious, expensive and practically impossible. So, indirect methods for estimating the transport parameters by pedo-transfer func...

Emergence of mcr-1 mediated colistin resistant Escherichia coli from a hospitalized patient in Bangladesh.

Journal of infection in developing countries
INTRODUCTION: The emergence of plasmid mediated mcr in bacteria has become global public health threat. Herein, we report a mcr-1 positive E. coli in normal human flora from a patient admitted in Dhaka Medical College Hospital (DMCH).

Detecting Developmental Delay and Autism Through Machine Learning Models Using Home Videos of Bangladeshi Children: Development and Validation Study.

Journal of medical Internet research
BACKGROUND: Autism spectrum disorder (ASD) is currently diagnosed using qualitative methods that measure between 20-100 behaviors, can span multiple appointments with trained clinicians, and take several hours to complete. In our previous work, we de...

Impact of health policy reforms on telemedicine and AI integration for early cancer detection among low-income populations in South Asia: A comparative policy analysis.

African journal of reproductive health
Early cancer detection remains a major challenge in low- and middle-income countries (LMICs), where late diagnoses and unequal healthcare access are widespread. While digital innovations such as telemedicine and artificial intelligence (AI) offer sig...